Use as the docs-priming stage of the Butterbase journey, immediately after journey-preflight and before the first build stage. Reads the plan to discover which capabilities the app uses, calls butterbase_docs once per relevant topic, and caches a summary the build stages can re-read.
npx skills add https://github.com/butterbase-ai/butterbase-skills --skill journey-docs
A short, mechanical priming step. The goal is that every downstream stage starts with the relevant docs already in the conversation, so the model doesn't invent API shapes.
Invoke automatically after journey-preflight returns. Also invoke standalone (/butterbase-skills:journey-docs) any time the user changes the plan or you realize a stage is using a capability you haven't refreshed this session.
docs/butterbase/02-plan.md. Identify every Butterbase capability in use (Tables → schema; RLS → auth; Auth → auth; Storage → storage; Functions → functions; AI → ai; RAG → rag; Realtime → realtime; Durable → functions; Frontend → frontend; Integrations → integrations; Substrate → substrate; Payments → billing).butterbase_docs per topic. For each unique topic from step 1, call butterbase_docs with that topic argument. Skip duplicates.docs/butterbase/03b-docs-cache.md with this structure: ---
primed_at: <ISO timestamp>
topics: [<comma-separated list>]
---
# Docs Cache
## <topic-1>
<one-paragraph summary of what the MCP doc says — key endpoints, common patterns, gotchas>
URL: https://docs.butterbase.ai/<area>
## <topic-2>
...
00-state.md. Tick the docs row."Primed docs for: schema, auth, storage, functions. Cache at docs/butterbase/03b-docs-cache.md."butterbase_docs with topic: "all". Burns context. Call once per relevant topic instead.Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take butterbase-ai/journey-docs from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.